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There's myriad of accessible information deposited in Deep Web, and the amount of the information is increasing rapidly. With the development of web application, there're more and more online databases, which make Deep Web a hot research topic. For the convenience of searching information in Scientific Data Sharing Platform, this paper does research of Deep Web application, and presents a system architecture...
To relieve "News Information Overload", classification, summarization and recommendation techniques have been proposed. However, these techniques fail to provide sufficient semantic information about news events. In this paper, considering5W1H (Who, What, Whom, When, Where and How), the full list of elements of a news article, we propose a novel approach to extract event semantic elements...
Within this paper we introduce a framework for semi- to full-automatic discovery and acquisition of bag-of-words style interest profiles from openly accessible Social Web communities. To do such, we construct a semantic taxonomy search tree from target domain (domain towards which we're acquiring profiles for), starting with generic concepts at root down to specific-level instances at leaves, then...
This paper asks which of White's (2009) three disciplines and relative valuation orders does the Singapore blogosphere adhere to. Analysing not just the hyperlink connections but the textual discourse; and in doing so attempts to highlight certain limitations of using automated data mining and analysis software. Using the Singapore blogosphere, described by Lin, Sundaram, Chi, Tatemura, and Tseng,...
The world has fundamentally changed as the Internet has become a universal means of communication. The Web is a huge virtual space where to express individual opinions and influence any aspect of life. Internet contains a wealth of data that can be mined to detect valuable opinions, with implications even in the political arena. Nowadays the Web sources are more accessible and valuable than ever before,...
Social tags are annotations for Web pages collaboratively added by users. It will be much easier to understand the meaning of Web pages and classify them according to their tags. The precision in retrieving Web pages may also increase using such tags. Nowadays social tags are mostly annotated manually by users via social bookmarking Web sites. Such manual annotation process may produce diverse, redundant,...
Social networks of the Web 2.0 have become global (e.g. FaceBook, MSN). In 1977, L. C. FREEMAN published the first generic metrics for Social Networks Analysis (SNA), mainly based on static graph-mining models. The objective of our work is to introduce new dynamic SNA models dedicated to SNA and to take the conceptual aspects of enterprises and institutions social graph into account. Our work is based...
This paper proposes a new method to cluster law texts based on referential relation of laws. We extract law entities (an entity represents a law) and their referential relation from law texts. Then SimRank algorithm is applied to calculate law entity's similarity through referential relation and law clustering is carried out based on the SimRank similarity. This is the first time to apply SimRank...
It is important to do research on the source trustworthiness of the massive data under network environment. A detection method of source trustworthiness in text is proposed and designed based on cognitive hash. Based on the HowNet semantic features, this paper designs a text cognitive hash, and proposes a method evaluating feasible hash distance. Experimental results show the effectiveness of the...
The discrepancies among the spectral range of the component bands of MHSRRSI will result in remarkable differences of the response extent to detect edges of geographical features. Considering the unique property of each color space, an improved Canny operator has been proposed which is available to detect and extract vector or scalar edges from MHSRRSI in weighted color space ( such as RGB, linear...
Making the semantic description and automatic semantic annotation of the image which contains rich contents and intuitive expression is a research subject that is challenging. It is a key technology of realizing fast and effective image retrieval and a research focusing on cross media mining. Also it has great application value in various kinds of fields. This paper studies and discusses image media...
Ontologies are an effective means to formally specify and constrain knowledge. They have proved their utility in various data mining applications, especially in annotating text to render it machine interpretable. More challenging research perspectives arise when ontologies are used to annotate images where the information is encoded in numeric pixel values rather than in natural language. Current...
As scientific achievements in the area of Healthcare have evolved during the last decade, inevitably there has been an increase of treatment quality. One of the challenges to be confronted is the personalization of treatment since each patient constitutes a unique case. The personalization requires the continuous reconfiguration of the treatment schemes since the clinical status of each patient and...
Recommendation systems are special personalization tools that help users to find interesting information and services in complex online shops. Even though today's e-commerce environments have drastically evolved and now incorporate techniques from other domains and application areas such as Web mining, semantics, artificial intelligence, user modeling and profiling, etc. setting up a successful recommendation...
Data preparation is an important part of the mining process. This paper describes MIDAS, an agent framework for intelligent data processing. The objective framework is to provide end users automated data processing services such as subsetting and data format translation by coupling Earth science markup language (ESML) interchange technology and ontologies. These ontology driven agents guide the user...
The Semantic Web and Multi-Agent are effective means for constructing information retrieval systems. Despite a great deal of research, a number of challenges still exist before making Semantic Web and agent-based computing a widely accepted in information retrieval practice. In order to solve the problem of "difficult to feedback useful information to users", the paper developed a new information...
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